An art of observing the ground surface from a height by an observation device, which is installed in a man-made satellite or an airplane, is called the remote sensing. In the remote sensing, there are many cases that intensity of the electromagnetic wave such as light or the like, which is emitted from an area having a predetermined size on the ground surface, is observed. Moreover, there are many cases that, regarding an observation result which is obtained by the remote sensing, an observation value is stored as pixel values of plural pixels composing an image (observation image). The pixel value is a value of a pixel which, in the observation image, is corresponding to a position according to an arrangement on the ground surface of the observed area. Particularly, in the case that the observation device is an image sensor, the observation result is generated as an image. A pixel value of a pixel, which is included by the image, is an observation value which is outputted by a light receiving element of the image sensor when the light receiving element receives intensity of observation light emitted in an incident direction of the light receiving element. Here, in the case that the pixel value is composed of at least a value which expresses radiance for each of observed wavelength bands, the value which expresses the radiance is also denoted as a radiance value. There are many cases that observation is carried out by using a filter which selectively transmits an electromagnetic wave having a wavelength within a wavelength band existing in a specified range. In this case, intensity of the electromagnetic wave, which is observed for each wavelength band, is obtained as the observation image by using a plurality of filters which have different wavelength bands for transmitting the electromagnetic wave.
As an application by which it is expected to utilize the observation image, farming support, resource exploration, or the like is exemplified. In order to realize the farming support, the resource exploration or the like with preciseness, it is necessary to obtain correct information on an object existing on the ground surface such as a farm product, an ore or the like. However, an observation value which is obtained as the observation image is influenced by radiance of illumination due to sunlight, absorption by the atmosphere and scattering by the atmosphere in addition to reflection from a surface of observation target. Therefore, the observation value is expressed by a formula which includes, in addition to the surface reflectance of an object corresponding to the observation target, the intensity of the illumination due to the sunlight, a component depending on the transmittance of the atmosphere's transmitting the electromagnetic wave, and a component of the electromagnetic wave which is scattered by the atmosphere and is inputted into the sensor. However, the intensity of the illumination due to the sunlight, the transmittance of the atmosphere, and the light scattered by the atmosphere are fluctuated by an environmental condition such as a fluctuation of an altitude of the sun, a fluctuation of a state of the atmosphere or the like. Therefore, in order to obtain accurate information on the object which exists on the ground surface, it is necessary to calculate an environment fluctuation component which does not depend on the object on the ground surface and remove the environment fluctuation component. Formula. 1 is a formula which expresses influence of the environment condition on the observed electromagnetic wave (observation light).L(λ)=α(λ)R(λ)+β(λ)  [Formula. 1]
In Formula. 1, L(λ) is a radiance value of the observation light for each wavelength λ. R(λ) is the surface reflectance of the object which exists on the ground surface. As shown by Formula. 1, the environment fluctuation component is mainly classified into two components. That is, in the case that the surface reflectance of the object existing on the ground surface is denoted as R(λ), one is a component α(λ) which is expressed as a coefficient of R(λ), and the other is a component β(λ) which is represented as an addition term to α(λ)R(λ). Out of the components, the coefficient component α(λ) is a component which relates to the intensity of illumination due to the sunlight and the transmittance of the electromagnetic wave which is transmitted by the atmosphere. The addition term component β(λ) expressed as an additional term is a component which is the observation light reaching the image sensor with no reflection from the object existing on the ground surface like the sunlight scattered by the atmosphere, and which expresses an optical path radiance. The relation shown by Formula. 1 is satisfied by an observation value which is observed in any wavelength band.
FIG. 5 is a diagram showing a relation between the observation light and the environment fluctuation component (environment noise), which is expressed as the coefficient term component and the addition term component, in the image which is photographed at the height. As shown in FIG. 5, the radiance value L(λ) of the observation light is a value which is obtained by multiplying the surface reflectance R(λ) of the object existing on the ground surface by the coefficient component α(λ), and adding the addition term component β(λ) (optical path radiance) to the component (reflection light reflected from the ground surface) which is corresponding to the multiplication result.
As mentioned above, in order to obtain the correct information on the object existing on the ground surface, it is necessary to calculate the environment fluctuation component which does not depend on the object existing on the ground surface, and afterward to remove the environment component from the observation light. Therefore, there is increasing expectation for an art of calculating the environment fluctuation component with a high degree of accuracy.
As an example of the above-mentioned art, PTL 1 discloses an image processing device which calculates an optical path radiance on the basis of the observation image including the optical path radiance, and corrects the optical path radiance by using the optical path radiance which is calculated on the basis of the observation image. The image processing device makes the minimum pixel value L(γ) out of the observation image in a wavelength band γ a calculation value of the optical path radiance.
FIG. 6 is a block diagram showing a configuration of an image information processing device 4 which uses the art disclosed by PTL 1. The image information processing device 4 includes an image reading unit 41, a dark pixel identification unit 42, a sensor parameter storage unit 43 and an atmosphere propagation correction unit 44. The image reading unit 41 reads the observation image from an image supply device 5. The dark pixel identification unit 42 extracts the minimum pixel value out of the inputted observation image for each wavelength band γ. The dark pixel identification unit 42 makes the smallest pixel value, which is extracted for each wavelength band γ, a calculation value βW(γ) of the optical path radiance. The sensor parameter storage unit 43 stores an atmosphere transmittance τ(γ) in each wavelength band. The atmosphere propagation correction unit 44 subtracts the calculation value βW(γ) of the optical path radiance in each wavelength band γ from the radiance value L(γ) for all pixels of the observation image.
Then, the atmosphere propagation correction unit 44 generates an optical path radiance correction image by dividing the subtraction result by the atmosphere transmittance τ(γ), which is stored by the sensor parameter storage unit 43, in each wavelength band γ. The atmosphere propagation correction unit 44 outputs the generated optical path radiance correction image to an output device 6.